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Abstract Developing machine learning (ML) methods for healthcare predictive modeling requires absolute explainability and transparency to build trust and accountability. Graphical models (GM) are key tools for this but face challenges like small sample sizes, mixed variables, and latent confounders. This paper presents a novel learning framework addressing these challenges by integrating latent variables using fast causal inference (FCI), accommodating mixed variables with predictive permutation conditional independence tests (PPCIT), and employing a systematic graphical embedding approach leveraging expert knowledge. This method ensures a transparent model structure and an explainable feature selection and modeling approach, achieving competitive prediction performance. For real-world validation, data of hospital-acquired pressure injuries (HAPI) among individuals with spinal cord injury (SCI) were used, where the approach achieved a balanced accuracy of 0.941 and an AUC of 0.983, outperforming most benchmarks. The PPCIT method also demonstrated superior accuracy and scalability over other benchmarks in causal discovery validation on synthetic datasets that closely resemble our real dataset. This holistic framework effectively addresses the challenges of mixed variables and explainable predictive modeling for disease onset, which is crucial for enabling transparency and interpretability in ML-based healthcare.

IntroductionPhysical exercise and gravitational load affect the activity of the cardiovascular system. How these factors interact with one another is still poorly understood. Here we investigate how the cardiovascular system responds to leg-press exercise during head-down tilt, a posture that reduces orthostatic stress, limits gravitational pooling, and increases central blood volume.MethodsSeventeen healthy participants performed leg-press exercise during head-down tilt at different combinations of resistive force, contraction frequency, and exercise duration (30 and 60 s), leading to different exercise power. Systolic (sBP), diastolic (dBP), mean arterial pressure (MAP), pulse pressure (PP) and heart rate (HR) were measured continuously. Cardiovascular responses were evaluated by comparing the values of these signals during exercise recovery to baseline. Mixed models were used to evaluate the effect of exercise power and of individual exercise parameter on the cardiovascular responses.ResultsImmediately after the exercise, we observed a clear undershoot in sBP (Δ = −7.78 ± 1.19 mmHg), dBP (Δ = −10.37 ± 0.84 mmHg), and MAP (Δ = −8.85 ± 0.85 mmHg), an overshoot in PP (Δ = 7.93 ± 1.13 mmHg), and elevated values of HR (Δ = 33.5 ± 0.94 bpm) compared to baseline (p 0.05). The responses of dBP, MAP and HR were significantly modulated by exercise power (correlation coefficients: rdBP = −0.34, rMAP = −0.25, rHR = 0.52, p

After a neurological injury, neurorehabilitation aims to restore sensorimotor function of patients. Technological assessments can provide high-quality data on a patient’s performance and support clinical decision making towards the most appropriate therapy. In this study, the ArmeoPower, a robotic exoskeleton for the upper extremities, was used to assess 12 neurological patients and 31 non-disabled participants performing various standardized single joint and frontal plane game-like exercises. From the collected data, kinematic metrics (End-Point Error, Hand-Path Ratio, reaction time, stability, Number of Velocity Peaks, peak, and mean Velocity) and the game score, were calculated and analyzed according to three criteria: the reliability (a), the difference between patients and non-disabled participants (b), as well as the influence of robotic movement assistance (c). In total, 39 metrics were analyzed and the following five most promising assessment variables for different exercises could be identified based on the three above-mentioned criteria: smoothness (RainMug (wrist)), mean speed (RainMug (wrist)), reaction time (Goalkeeper), maximum speed (HighFlyer (elbow)) and accuracy (Connect the dots), with the former showing good validity (rho=0.82, p=0.02) when comparing to the patient’s severity level. The results demonstrate feasibility to extract and analyze various kinematic metrics from the ArmeoPower, which can provide quantitative information about human performance during training and therapy. The generated data increases the understanding of the patient’s movement and can be used in the future in clinical research for better performance evaluation and providing more feedback options, leading towards a more personalized and patient-centric therapy.

Abstract Background Pressure Injuries are not exclusively an adult phenomenon; various risk factors contribute to a high prevalence rate of 43% in the neonatal and pediatric intensive care population. Effective preventive measures in this population are limited. Methods We performed a pilot study to analyze the distribution and localization of support surface interface pressures in neonates in a pediatric intensive care unit (PICU). The hypothesis was that pressure redistribution by a novel air mattress would reduce pressure peaks in critical neonates. The measurements were conducted in a 27-bed level III PICU between November and December 2020. This included measuring pressure distribution and pressure peaks for five neonates positioned on either a state-of-the-art foam mattress or a new prototype air mattress. Results We confirmed that the pressure peaks were significantly reduced using the prototype air mattress, compared with the state-of-the-art foam mattress. The reduction of mean pressure values was 9–29%, while the reduction of the highest 10% of pressure values was 23–41%. Conclusions The journey to an effective, optimal, and approved product for severely ill neonates to reduce Pressure Injuries is challenging. However, a crucial step was completed by this pilot study with the first pressure measurements in a real-world setting and the successful realization of a decrease in pressure peaks obtained using a prototype air mattress.

Abstract Background Walking impairments are a common consequence of neurological disorders and are assessed with clinical scores that suffer from several limitations. Robot-assisted locomotor training is becoming an established clinical practice. Besides training, these devices could be used for assessing walking ability in a controlled environment. Here, we propose an adaptive assist-as-needed (AAN) control for a treadmill-based robotic exoskeleton, the Lokomat, that reduces the support of the device (body weight support and impedance of the robotic joints) based on the ability of the patient to follow a gait pattern displayed on screen. We hypothesize that the converged values of robotic support provide valid and reliable information about individuals’ walking ability. Methods Fifteen participants with spinal cord injury and twelve controls used the AAN software in the Lokomat twice within a week and were assessed using clinical scores (10MWT, TUG). We used a regression method to identify the robotic measure that could provide the most relevant information about walking ability and determined the test–retest reliability. We also checked whether this result could be extrapolated to non-ambulatory and to unimpaired subjects. Results The AAN controller could be used in patients with different injury severity levels. A linear model based on one variable (robotic knee stiffness at terminal swing) could explain 74% of the variance in the 10MWT and 61% in the TUG in ambulatory patients and showed good relative reliability but poor absolute reliability. Adding the variable ‘maximum hip flexor torque’ to the model increased the explained variance above 85%. This did not extend to non-ambulatory nor to able-bodied individuals, where variables related to stance phase and to push-off phase seem more relevant. Conclusions The novel AAN software for the Lokomat can be used to quantify the support required by a patient while performing robotic gait training. The adaptive software might enable more challenging training conditions tuned to the ability of the individuals. While the current implementation is not ready for assessment in clinical practice, we could demonstrate that this approach is safe, and it could be integrated as assist-as-needed training, rather than as assessment. Trial registration ClinicalTrials.gov Identifier: NCT02425332.

Introduction: Children and adolescents with neurological impairments face reduced participation and independence in daily life activities due to walking difficulties. Existing assistive devices often offer insufficient support, potentially leading to wheelchair dependence and limiting physical activity and daily life engagement. Mobile wearable robots, such as exoskeletons and exosuits, have shown promise in supporting adults during activities of daily living but are underexplored for children.Methods: We conducted a cross-sectional study to examine the potential of a cable-driven exosuit, the Myosuit, to enhance walking efficiency in adolescents with diverse ambulatory impairments. Each participant walked a course including up-hill, down-hill, level ground walking, and stairs ascending and descending, with and without the exosuit’s assistance. We monitored the time and step count to complete the course and the average heart rate and muscle activity. Additionally, we assessed the adolescents’ perspective on the exosuit’s utility using a visual analog scale.Results: Six adolescents completed the study. Although not statistically significant, five participants completed the course with the exosuit’s assistance in reduced time (time reduction range: [-3.87, 17.42]%, p-value: 0.08, effect size: 0.88). The number of steps taken decreased significantly with the Myosuit’s assistance (steps reduction range: [1.07, 15.71]%, p-value: 0.04, effect size: 0.90). Heart rate and muscle activity did not differ between Myosuit-assisted and unassisted conditions (p-value: 0.96 and 0.35, effect size: 0.02 and 0.42, respectively). Participants generally perceived reduced effort and increased safety with the Myosuit’s assistance, especially during tasks involving concentric contractions (e.g., walking uphill). Three participants expressed a willingness to use the Myosuit in daily life, while the others found it heavy or too conspicuous.Discussion: Increased walking speed without increasing physical effort when performing activities of daily living could lead to higher levels of participation and increased functional independence. Despite perceiving the benefits introduced by the exosuit’s assistance, adolescents reported the need for further modification of the device design before using it extensively at home and in the community.

Cable-driven exosuits have the potential to support individuals with motor disabilities across the continuum of care. When supporting a limb with a cable, force sensors are often used to measure tension. However, force sensors add cost, complexity, and distal components. This paper presents a design and control approach to remove the force sensor from an upper limb cable-driven exosuit. A mechanical design for the exosuit was developed to maximize passive transparency. Then, a data-driven friction identification was conducted on a mannequin test bench to design a model-based tension controller. Seventeen healthy participants raised and lowered their right arms to evaluate tension tracking, movement quality, and muscular effort. Questionnaires on discomfort, physical exertion, and fatigue were collected. The proposed strategy allowed tracking the desired assistive torque with a root mean square error of 0.71 Nm (18%) at 50% gravity support. During the raising phase, the electromyography signals of the anterior deltoid, trapezius, and pectoralis major were reduced on average compared to the no-suit condition by 30, 38, and 38%, respectively. The posterior deltoid activity was increased by 32% during lowering. Position tracking was not significantly altered, whereas movement smoothness significantly decreased. This work demonstrates the feasibility and effectiveness of removing the force sensor from a cable-driven exosuit. A significant increase in discomfort in the lower neck and right shoulder indicated that the ergonomics of the suit could be improved. Overall this work paves the way toward simpler and more affordable exosuits.

The incessant progress of robotic technology and rationalization of human manpower induces high expectations in society, but also resentment and even fear. In this paper, we present a quantitative normalized comparison of performance, to shine a light onto the pressing question, “How close is the current state of humanoid robotics to outperforming humans in their typical functions (e.g., locomotion, manipulation), and their underlying structures (e.g., actuators/muscles) in human-centered domains?” This is the most comprehensive comparison of the literature so far. Most state-of-the-art robotic structures required for visual, tactile, or vestibular perception outperform human structures at the cost of slightly higher mass and volume. Electromagnetic and fluidic actuation outperform human muscles w.r.t. speed, endurance, force density, and power density, excluding components for energy storage and conversion. Artificial joints and links can compete with the human skeleton. In contrast, the comparison of locomotion functions shows that robots are trailing behind in energy efficiency, operational time, and transportation costs. Robots are capable of obstacle negotiation, object manipulation, swimming, playing soccer, or vehicle operation. Despite the impressive advances of humanoid robots in the last two decades, current robots are not yet reaching the dexterity and versatility to cope with more complex manipulation and locomotion tasks (e.g., in confined spaces). We conclude that state-of-the-art humanoid robotics is far from matching the dexterity and versatility of human beings. Despite the outperforming technical structures, robot functions are inferior to human ones, even with tethered robots that could place heavy auxiliary components off-board. The persistent advances in robotics let us anticipate the diminishing of the gap.

Abstract Background Exosuits have been shown to reduce metabolic cost of walking and to increase gait performance when used in clinical environment. Currently, these devices are transitioning to private use to facilitate independent training at home and in the community. However, their acceptance in unsupervised settings remains unclear. Therefore, the aim of this study was to investigate end-user perspectives and the adoption of an exosuit in domestic and community settings. Methods We conducted a mixed-method study to investigate the usability and user experience of an exosuit, the Myosuit. We leveraged on a cohort of seven expert users, who had the device available at home for at least 28 days. Each participant completed two standardized questionnaires (SUS and QUEST) and one personalized, custom questionnaire. Furthermore, a semi-structured interview with each participant was recorded, verbatim transcribed and analyzed using descriptive thematic analysis. Data collected from device sensors quantified the frequency of use. Results A mean SUS score of 75.4 out of 100 was reported. Five participants scored above the threshold for above-average usability. Participants also expressed high satisfaction with most of the technical features in the QUEST with an average score of 4.1 (3.86–4.71) out of 5. Participants used the Myosuit mainly for walking outside and exercising at home. However, the frequency of use did not meet the recommendations for physical activity established by the World Health Organization. Five participants used the Myosuit approximately once per week. The two other participants integrated the device in their daily life and used the Myosuit to a greater extent (approx. five times per week). Major factors that prevented an extensive use of the technology were: (i) difficulties in donning that led to (ii) lack of independence and (iii) lack of motivation in exercising. Conclusions Although usable for various activities and well perceived, the adoption of the exosuit in domestic and community settings is yet limited. Use outside the clinic poses further challenges that should be considered when developing new wearable robots. Primarily, design should meet the users' claim for independence and increased adjustability of the device.

Abstract Background Stroke related motor function deficits affect patients' likelihood of returning to professional activities, limit their participation in society and functionality in daily living. Hence, robot-aided gait rehabilitation needs to be fruitful and effective from a motor learning perspective. For this reason, optimal human–robot interaction strategies are necessary to foster neuroplastic shaping during therapy. Therefore, we performed a systematic search on the effects of different control algorithms on quantitative objective gait parameters of post-acute stroke patients. Methods We conducted a systematic search on four electronic databases using the Population Intervention Comparison and Outcome format. The heterogeneity of performance assessment, study designs and patients’ numerosity prevented the possibility to conduct a rigorous meta-analysis, thus, the results were presented through narrative synthesis. Results A total of 31 studies (out of 1036) met the inclusion criteria, without applying any temporal constraints. No controller preference with respect to gait parameters improvements was found. However, preferred solutions were encountered in the implementation of force control strategies mostly on rigid devices in therapeutic scenarios. Conversely, soft devices, which were all position-controlled, were found to be more commonly used in assistive scenarios. The effect of different controllers on gait could not be evaluated since conspicuous heterogeneity was found for both performance metrics and study designs. Conclusions Overall, due to the impossibility of performing a meta-analysis, this systematic review calls for an outcome standardisation in the evaluation of robot-aided gait rehabilitation. This could allow for the comparison of adaptive and human-dependent controllers with conventional ones, identifying the most suitable control strategies for specific pathologic gait patterns. This latter aspect could bolster individualized and personalized choices of control strategies during the therapeutic or assistive path.

Abstract Aims The aim of this pilot study was to investigate the safety, feasibility, tolerability, and acceptability of an assisted mobilization of advanced heart failure patients, using a lightweight, exoskeleton‐type robot (Myosuit, MyoSwiss AG, Zurich, Switzerland). Methods and results Twenty patients in functional NYHA class III performed activities of daily life (ADL, n = 10) or participated in a single, standardized, 60 min rehabilitation exercise unit (REU, n = 10) with and without the Myosuit. The outcome assessment included the evaluation of vital signs, adverse events, rates of perceived exertion and dyspnoea (RPE, RPD), the ability to perform ADL or REU, and the individual acceptability. The mean age of the subjects was 49.4 (±11.0) years; 80% were male. The mean left ventricular ejection fraction was 22.1% (±7.4%) and the median NT‐proBNP 2054 pg/mL (IQR 677, 3270 pg/mL). In all patients, mobilization with the Myosuit was feasible independently or with minor support. The mean individual difference in the total walking distance of the patients without and with robotic assistance was −26.5 m (95% confidence interval (CI) −142 to 78 m, P = 0.241). No adverse events occurred. RPE and RPD showed no significant difference with or without the device (ADL: RPE −0.1 m, 95% CI −1.42 to 1.62, P = 0.932 and RPD −0.95 m, 95% CI −0.38 to 2.28, P = 0.141; REU: RPE 1.1 m, 95% CI −2.90 to 0.70, P = 0.201 and RPD 0.5 m, 95% CI −2.02 to 1.02, P = 0.435). All median responses in the acceptability questionnaire were positive. The patients felt safe and enjoyed the experience; 85% would be interested in participating in robot‐assisted training on a regular basis. Conclusion This feasibility pilot trial provides first indications that a robotic exoskeleton‐assisted mobilization of patients with advanced heart failure is safe, feasible, well‐tolerated, and well‐accepted. The results are highly encouraging to further pursue this innovative approach in rehabilitation programmes. This trial was registered at ClinicalTrials.gov: NCT04839133.

Abstract Background Wearable robots have been shown to improve the efficiency of walking in diverse scenarios. However, it is unclear how much practice is needed to fully adapt to robotic assistance, and which neuromotor processes underly this adaptation. Familiarization strategies for novice users, robotic optimization techniques (e.g. human-in-the-loop), and meaningful comparative assessments depend on this understanding. Methods To better understand the process of motor adaptation to robotic assistance, we analyzed the energy expenditure, gait kinematics, stride times, and muscle activities of eight naïve unimpaired participants across three 20-min sessions of robot-assisted walking. Experimental outcomes were analyzed with linear mixed effect models and statistical parametric mapping techniques. Results Most of the participants’ kinematic and muscular adaptation occurred within the first minute of assisted walking. After ten minutes, or 880 steps, the energetic benefits of assistance were realized (an average of 5.1% (SD 2.4%) reduction in energy expenditure compared to unassisted walking). Motor adaptation was likely driven by the formation of an internal model for feedforward motor control as evidenced by the reduction of burst-like muscle activity at the cyclic end of robotic assistance and an increase in arm-swing asymmetry previously associated with increased cognitive load. Conclusion Humans appear to adapt to walking assistance from a wearable robot over 880 steps by forming an internal model for feedforward control. The observed adaptation to the wearable robot is well-described by existing three-stage models that start from a cognitive stage, continue with an associative stage, and end in autonomous task execution. Trial registration Not applicable.

Abstract Background Scapular dyskinesis, i.e., the deviant mobility or function of the scapula, hampers upper limb function in daily life. A typical sign of scapular dyskinesis is a scapula alata—a protrusion of the shoulder blade during arm elevation. While some reversible causes of scapula alata can be treated with therapy, other, irreversible causes require invasive surgical interventions. When surgery is not an option, however, severe limitations arise as standard approaches for assisting the scapula in daily life do not exist. The aim of this study was to quantify functional improvements when external, i.e., non-invasive, scapula assistance is provided. Methods The study was designed as a randomized controlled crossover trial. Eight participants with a scapula alata due to muscular dystrophy performed arm elevations in shoulder flexion and abduction while unassisted (baseline), externally assisted by a trained therapist, and externally assisted by a novel, textile-based scapula orthosis. Results With therapist assistance, average arm elevation increased by 17.3° in flexion (p

Abstract Most wearable robots that assist the gait of workers, soldiers, athletes, and hobbyists are developed towards a vision of outdoor, overground walking. However, so far, these devices have predominantly been tested indoors on laboratory treadmills. It is unclear whether treadmill-based laboratory tests are an accurate representation of overground ambulation outdoors with respect to essential outcomes such as the metabolic benefits of robotic assistance. In this study, we investigated the metabolic benefits of the Myosuit, a wearable robot that assists hip and knee extension during the stance phase of gait, for eight unimpaired participants during uphill walking trials in three settings: outside, on a self-paced treadmill with a virtual reality display, and on a standard treadmill at a fixed gait speed. The relative metabolic reduction with Myosuit assistance was most pronounced in the outside setting at − 10.6% and significantly larger than in the two treadmill settings (− 6.9%, p = 0.015 and − 6.2%, p = 0.008). This indicates that treadmill tests likely result in systematically low estimate for the true metabolic benefits of wearable robots during outside, overground walking. Hence, wearable robots should preferably be tested in an outdoor environment to obtain more representative—and ultimately more favorable—results with respect to the metabolic benefit of robotic gait assistance.

The use of stereophotogrammetry systems is challenging when targeting children’s gait analysis due to the time required and the need to keep physical markers in place. For this reason, marker-less photoelectric systems appear to be a solution for accurate and fast gait analysis in youth. The aim of this study is to validate a photoelectric system and its configurations (LED filter setting) on healthy children, comparing the kinematic gait parameters with those obtained from a three-dimensional stereophotogrammetry system. Twenty-seven healthy children were enrolled. Three LED filter settings for the OptoGait were compared to the BTS P6000. The analysis included the non-parametric 80% limits of agreement and the intraclass correlation coefficient (ICC). Additionally, normalised limits of agreement and bias (NLoAs and Nbias) were compared to the clinical experience of physical therapists (i.e., assuming an error lower than 5% is acceptable). ICCs showed excellent consistency for most of the parameters and filter settings; NLoAs varied between 1.39% and 12.62%. An inverse association between the number of LEDs for filter setting and the bias values was also observed. Observations confirm the validity of the OptoGait system for the evaluation of spatiotemporal gait parameters in children.

Abstract Background Physical activity is a recommended part of treatment for numerous neurological and neuromuscular disorders. Yet, many individuals with limited mobility are not able to meet the recommended activity levels. Lightweight, wearable robots like the Myosuit promise to facilitate functional ambulation and thereby physical activity. However, there is limited evidence of the safety and feasibility of training with such devices. Methods Twelve participants with diverse motor disorders and the ability to walk for at least 10 m were enrolled in this uncontrolled case series study. The study protocol included five training sessions with a net training time of 45 min each. Primary outcomes were the feasibility of engaging in training with the Myosuit, the occurrence of adverse events, and participant retention. As secondary outcomes, we analyzed the walking speed using the 10-m Walk Test (10MWT) and for three participants, walking endurance using the 2-min Walk Tests. Results Eight out of 12 participants completed the entire study protocol. Three participants withdrew from the study or were excluded for reasons unrelated to the study. One participant withdrew because of an unsafe feeling when walking with the Myosuit. No adverse events occurred during the study period for any of the participants and all scheduled trainings were completed. For five out of the eight participants that completed the full study, the walking speed when using the Myosuit was higher than to their baseline walking speed. Conclusions Activity-based training with the Myosuit appears to be safe, feasible, and well-tolerated by individuals with diverse motor disorders.

Abstract Purpose Avoiding supine position can reduce snoring in most habitual snorers. However, devices that restrict the sleeping position cause discomfort or disrupt sleep resulting in low compliance. Therefore, mechanisms, which lift the trunk of the user without disturbing sleep, have been proposed. We present the first study, which investigates whether individual interventions provided by beds with lifting mechanisms are able to stop snoring (success rate) and whether they reduce the snoring index (number of total snores divided by total time in bed) using a repeated measures design. In addition, we investigated whether the intervention is interfering with the subjective sleep quality. Methods Twenty-two subjects were observed for four nights (adaptation, baseline, and two intervention nights). During intervention nights, the bed lifted the trunk of the user in closed-loop manner. Subjects were divided in three groups (non-snorer, snorer one, and snorer two). Non-snorers were lifted by the bed at random time points during the night. In group snorer one, a stepwise increase of the bed inclination was compared with going directly to a randomly selected angle. In group snorer two, the influence of a small inclination angle (10 ∘) and a big inclination angle (20 ∘) was compared. Results Snoring was stopped successfully in 22% (small angle) and 67% (big angle) of the interventions. This did not lead to a significant reduction in the snoring index. The subjective sleep quality was not reduced by the intervention. Conclusion The anti-snoring bed is able to stop individual episodes of habitual snoring without reducing the subjective sleep quality. Trial Registration https://clinicaltrials.gov , no. NCT04053738, registered 12 August 2019 - Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT04053738 .

Abstract Background Sleep-related rhythmic movement disorder is characterized by repetitive gross-motor movements at sleep onset or during sleep, which result in clinical consequences such as impact on daytime functioning and injury. No well-established therapies exist today. Substituting the patient’s movements with external sensory stimulation may offer a treatment modality. The aim of the current study was to test the feasibility and acceptability of vestibular stimulation using a rocking bed (Somnomat) in children with rhythmic movement disorder and to assess children’s movement preference. Methods Children with rhythmic movement disorder (n = 6, Age: 5–14 years) were studied over three nights in a sleep laboratory: adaptation night (normal bed) and randomised-order baseline (Somnomat) and intervention nights (Somnomat). Child’s preferred movement direction (head-to-toe or side-to-side) and frequency (between 0.25 and 2 Hz), determined during an afternoon protocol, were applied using the Somnomat for 1 h after lights out, and in response to subsequent episodes of rhythmic movement during intervention nights. Comfort assessed using a questionnaire, and objective sleep parameters assessed using videosomnography, were compared. Results The participants’ sometimes violent rhythmic movements did not disturb device performance. All children rated intervention nights equally or more comfortable than baseline nights. Self-reported sleep quality, as well as the number and duration of movement episodes did not significantly differ between baseline and intervention nights. Conclusions Providing rocking movements using the Somnomat is both technically feasible and acceptable to the target population. The therapeutic value of this novel stimulus substitution for rhythmic movement disorder should now be evaluated in a larger sample over a longer period in the home setting. Trial registration The trial was retrospectively registered at clinicaltrials.gov ( NCT03528096 ) on May 17th 2018.

Abstract Background Tremor is the most common movement disorder with the highest prevalence in the upper limbs. The mechanical suppression of involuntary movements is an alternative and additional treatment to medication or surgery. Here we present a new, soft, lightweight, task asjustable and passive orthosis for tremor suppression. Methods A new concept of a manual, textile-based, passive orthosis was designed with an integrated, task adjustable, air-filled structure, which can easily be inflated or deflated on-demand for a certain daily activity. The air-filled structure is placed on the dorsal side of the wrist and gets bent and compressed by movements when inflated. In a constant volume air-filled structure, air pressure increases while it is inflating, creating a counterforce to the compression caused by bending. We characterised the air-filled structure stiffness by measuring the reaction torque as a function of the angle of deflection on a test bench. Furthermore, we evaluated the efficacy of the developed passive soft orthosis by analysing the suppression of involuntary movements in the wrist of a tremor-affected patient during different activities of daily living (i.e. by calculating the power spectral densities of acceleration). Results By putting special emphasis on the comfort and wearability of the orthosis, we achieved a lightweight design (33 g). The measurements of the angular deflection and resulting reaction torques show non-linear, hysteretic, behaviour, as well as linear behaviour with a coefficient of determination (R2) between 0.95 and 0.99. Furthermore, we demonstrated that the soft orthosis significantly reduces tremor power for daily living activities, such as drinking from a cup, pouring water and drawing a spiral, by 74 to 82% (p = 0.03); confirmed by subjective tremor-reducing perception by the patient. Conclusion The orthosis we developed is a lightweight and unobtrusive assistive technology, which suppresses involuntary movements and shows high wearability properties, with the potential to be comfortable. This air-structure technology could also be applied to other movement disorders, like spasticity, or even be integrated into future exoskeletons and exosuits for the implementation of variable stiffness in the systems.

Abstract Background Arm weight compensation with rehabilitation robots for stroke patients has been successfully used to increase the active range of motion and reduce the effects of pathological muscle synergies. However, the differences in structure, performance, and control algorithms among the existing robotic platforms make it hard to effectively assess and compare human arm weight relief. In this paper, we introduce criteria for ideal arm weight compensation, and furthermore, we propose and analyze three distinct arm weight compensation methods (Average, Full, Equilibrium) in the arm rehabilitation exoskeleton ’ARMin’. The effect of the best performing method was validated in chronic stroke subjects to increase the active range of motion in three dimensional space. Methods All three methods are based on arm models that are generalizable for use in different robotic devices and allow individualized adaptation to the subject by model parameters. The first method Average uses anthropometric tables to determine subject-specific parameters. The parameters for the second method Full are estimated based on force sensor data in predefined resting poses. The third method Equilibrium estimates parameters by optimizing an equilibrium of force/torque equations in a predefined resting pose. The parameters for all three methods were first determined and optimized for temporal and spatial estimation sensitivity. Then, the three methods were compared in a randomized single-center study with respect to the remaining electromyography (EMG) activity of 31 healthy participants who performed five arm poses covering the full range of motion with the exoskeleton robot. The best method was chosen for feasibility tests with three stroke patients. In detail, the influence of arm weight compensation on the three dimensional workspace was assessed by measuring of the horizontal workspace at three different height levels in stroke patients. Results All three arm weight compensation methods reduced the mean EMG activity of healthy subjects to at least 49% compared with the no compensation reference. The Equilibrium method outperformed the Average and the Full methods with a highly significant reduction in mean EMG activity by 19% and 28% respectively. However, upon direct comparison, each method has its own individual advantages such as in set-up time, cost, or required technology. The horizontal workspace assessment in poststroke patients with the Equilibrium method revealed potential workspace size-dependence of arm height, while weight compensation helped maximize the workspace as much as possible. Conclusion Different arm weight compensation methods were developed according to initially defined criteria. The methods were then analyzed with respect to their sensitivity and required technology. In general, weight compensation performance improved with the level of technology, but increased cost and calibration efforts. This study reports a systematic way to analyze the efficacy of different weight compensation methods using EMG. Additionally, the feasibility of the best method, Equilibrium, was shown by testing with three stroke patients. In this test, a height dependence of the workspace size also seemed to be present, which further highlights the importance of patient-specific weight compensation, particularly for training at different arm heights. Trial registration ClinicalTrials.gov,NCT02720341. Registered 25 March 2016

Assistive forces transmitted from wearable robots to the robot’s users are often defined by controllers that rely on the accurate estimation of the human posture. The compliant nature of the human–robot interface can negatively affect the robot’s ability to estimate the posture. In this article, we present a novel algorithm that uses machine learning to correct these errors in posture estimation. For that, we recorded motion capture data and robot performance data from a group of participants (n = 8; 4 females) who walked on a treadmill while wearing a wearable robot, the Myosuit. Participants walked on level ground at various gait speeds and levels of support from the Myosuit. We used optical motion capture data to measure the relative displacement between the person and the Myosuit. We then combined this data with data derived from the robot to train a model, using a grading boosting algorithm (XGBoost), that corrected for the mechanical compliance errors in posture estimation. For the Myosuit controller, we were particularly interested in the angle of the thigh segment. Using our algorithm, the estimated thigh segment’s angle RMS error was reduced from 6.3° (2.3°) to 2.5° (1.0°), mean (standard deviation). The average maximum error was reduced from 13.1° (4.9°) to 5.9° (2.1°). These improvements in posture estimation were observed for all of the considered assistance force levels and walking speeds. This suggests that ML-based algorithms provide a promising opportunity to be used in combination with wearable-robot sensors for an accurate user posture estimation.

Abstract Introduction Tremor is the most common movement disorder, affecting 5.6% of the population with Parkinson’s disease or essential tremor over the age of 65. Conventionally, tremor diseases like Parkinson’s are treated with medication. An alternative non-invasive symptom treatment is the mechanical suppression of the oscillation movement. The purpose of this review is to identify the weaknesses of past wearable tremor-suppression orthoses for the upper limb and identify the need for further research and developments. Method A systematic literature search was conducted by performing a keyword combination search of the title, abstract and keyword sections in the four databases Web of Science, MedLine, Scopus, and ProQuest. Initially, the retrieved articles were selected by title and abstract using selection criteria. The same criteria were then applied to the full publication text. After the selection process, relevant information on the retrieved orthoses was isolated, sorted and analysed systematically. Results Forty-six papers, representing 21 orthoses, were identified and analysed according to the mechanical and ergonomic properties. The identified orthoses can be divided into 5 concepts and 16 functional prototypes, then subdivided further based upon their use of passive, semi-active, or active suppression mechanisms. Most of the orthoses concentrate on the wrist and elbow flexion and extension. They mainly rely on rigid structures and actuators while having tremor-suppression efficacies for tremorous subjects from 30 to 98% using power spectral density or other methods. Conclusion The comparison of tremor-suppression orthoses considered and mapped their various mechanical and ergonomic properties, including the degrees of freedom, weight, suppression characteristics, and efficacies. This review shows that most of the orthoses are bulky and heavy, with a non-adapted human-machine interface which can cause rejection by the user. The main challenge of the design of an effective, minimally intrusive and portable tremor-suppressing orthosis is the integration of compact, powerful, lightweight, and non-cumbersome suppression mechanisms. None of the existing prototypes combine all the desired characteristics. Future research should focus on novel suppression orthoses and mechanisms with compact dimensions and light weight in order to be less cumbersome while giving a good tremor-suppression performance.

Abstract Background We present a robot-assisted telerehabilitation system that allows for haptic interaction between therapist and patient over distance. It consists of two arm therapy robots. Attached to one robot the therapists can feel on their own arm the limitations of the patient’s arm which is attached to the other robot. Due to the exoskeleton structure of the robot, movements can be performed in the three-dimensional space. Methods Fifteen physical and occupational therapists tested this strategy, named “Beam-Me-In”, while using an exoskeleton robot connected to a second exoskeleton robot in the same room used by the study experimenter. Furthermore, the therapists assessed the level of impairment of recorded and simulated arm movements. They quantified four typical impairments of stroke patients: reduced range of motion (active and passive), resistance to passive movement, a lack of ability to fractionate a movement, and disturbed quality of movement. Results On a Likert Scale (0 to 5 points) therapists rated the “Beam-Me-In” strategy as a very useful medium (mode: 4 points) to evaluate a patient’s progress over time. The passive range of motion of the elbow joint was assessed with a mean absolute error of 4.9∘ (absolute precision error: 6.4∘). The active range of motion of the elbow was assessed with a mean absolute error of 4.9∘ (absolute precision error: 6.5∘). The resistance to passive movement (i.e. modified Tardieu Scale) and the lack of ability to fractionate a movement (i.e. quantification of pathological muscle synergies) was assessed with an inter-rater reliability of 0.930 and 0.948, respectively. Conclusions The “Beam-Me-In” strategy is a promising approach to complement robot-assisted movement training. It can serve as a platform to assess and identify abnormal movement patterns in patients. This is the first application of remote three-dimensional haptic assessmen t applied to telerehabilitation. Furthermore, the “Beam-Me-In” strategy has a potential to overcome barriers for therapists regarding robot-assisted telerehabilitation.

The growing field of soft wearable exosuits, is gradually gaining terrain and proposing new complementary solutions in assistive technology, with several advantages in terms of portability, kinematic transparency, ergonomics, and metabolic efficiency. Those are palatable benefits that can be exploited in several applications, ranging from strength and resistance augmentation in industrial scenarios, to assistance or rehabilitation for people with motor impairments. To be effective, however, an exosuit needs to synergistically work with the human and matching specific requirements in terms of both movements kinematics and dynamics: an accurate and timely intention-detection strategy is the paramount aspect which assume a fundamental importance for acceptance and usability of such technology. We previously proposed to tackle this challenge by means of a model-based myoelectric controller, treating the exosuit as an external muscular layer in parallel to the human biomechanics and as such, controlled by the same efferent motor commands of biological muscles. However, previous studies that used classical control methods, demonstrated that the level of device's intervention and effectiveness of task completion are not linearly related: therefore, using a newly implemented EMG-driven controller, we isolated and characterized the relationship between assistance magnitude and muscular benefits, with the goal to find a range of assistance which could make the controller versatile for both dynamic and static tasks. Ten healthy participants performed the experiment resembling functional daily activities living in separate assistance conditions: without the device's active support and with different levels of intervention by the exosuit. Higher assistance levels resulted in larger reductions in the activity of the muscles augmented by the suit actuation and a good performance in motion accuracy, despite involving a decrease of the movement velocities, with respect to the no assistance condition. Moreover, increasing torque magnitude by the exosuit resulted in a significant reduction in the biological torque at the elbow joint and in a progressive effective delay in the onset of muscular fatigue. Thus, contrarily to classical force and proportional myoelectric schemes, the implementation of an opportunely tailored EMG-driven model based controller affords to naturally match user's intention detection and provide an assistance level working symbiotically with the human biomechanics.

Abstract Background Physical and functional losses due to aging and diseases decrease human mobility, independence, and quality of life. This study is aimed at summarizing and quantifying these losses in order to motivate solutions to overcome them with a special focus on the possibilities by using lower limb exoskeletons. Methods A narrative literature review was performed to determine a broad range of mobility-related physical and functional measures that are affected by aging and selected cardiovascular, respiratory, musculoskeletal, and neurological diseases. Results The study identified that decreases in limb maximum muscle force and power (33% and 49%, respectively, 25–75 yrs) and in maximum oxygen consumption (40%, 20–80 yrs) occur for older adults compared to young adults. Reaction times more than double (18–90 yrs) and losses in the visual, vestibular, and somatosensory systems were reported. Additionally, we found decreases in steps per day (75%, 60–85 yrs), maximum walking speed (24% 25–75 yrs), and maximum six-minute and self-selected walking speed (38% and 21%, respectively, 20–85 yrs), while we found increases in the number of falls relative to the number of steps per day (800%), injuries due to falls (472%, 30–90 yrs) and deaths caused by fall (4000%, 65–90 yrs). Measures were identified to be worse for individuals with impaired mobility. Additional detrimental effects identified for them were the loss of upright standing and locomotion, freezing in movement, joint stress, pain, and changes in gait patterns. Discussion This review shows that aging and chronic conditions result in wide-ranging losses in physical and sensory capabilities. While the impact of these losses are relatively modest for level walking, they become limiting during more demanding tasks such as walking on inclined ground, climbing stairs, or walking over longer periods, and especially when coupled with a debilitating disease. As the physical and functional parameters are closely related, we believe that lost functional capabilities can be indirectly improved by training of the physical capabilities. However, assistive devices can supplement the lost functional capabilities directly by compensating for losses with propulsion, weight support, and balance support. Conclusions Exoskeletons are a new generation of assistive devices that have the potential to provide both, training capabilities and functional compensation, to enhance human mobility.

Abstract Background During functional electrical stimulation (FES) tasks with able-bodied (AB) participants, spatially distributed sequential stimulation (SDSS) has demonstrated substantial improvements in power output and fatigue properties compared to conventional single electrode stimulation (SES). The aim of this study was to compare the properties of SDSS and SES in participants with spinal cord injury (SCI) in a dynamic isokinetic knee extension task simulating knee movement during recumbent cycling. Method Using a case-series design, m. vastus lateralis and medialis of four participants with motor and sensory complete SCI (AIS A) were stimulated for 6 min on both legs with both electrode setups. With SES, target muscles were stimulated by a pair of electrodes. In SDSS, the distal electrodes were replaced by four small electrodes giving the same overall stimulation frequency and having the same total surface area. Torque was measured during knee extension by a dynamometer at an angular velocity of 110 deg/s. Mean power of the left and right sides (P m e a n L,R ) was calculated from all stimulated extensions for initial, final and all extensions. Fatigue is presented as an index value with respect to initial power from 1 to 0, whereby 1 means no fatigue. Results SDSS showed higher P m e a n L,R values for all four participants for all extensions (increases of 132% in participant P1, 100% in P2, 36% in P3 and 18% in P4 compared to SES) and for the initial phase (increases of 84%, 59%, 66%, and 16%, respectively). Fatigue resistance was better with SDSS for P1, P2 and P4 but worse for P3 (0.47 vs 0.35, 0.63 vs 0.49, 0.90 vs 0.82 and 0.59 vs 0.77, respectively). Conclusion Consistently higher P m e a n L,R was observed for all four participants for initial and overall contractions using SDSS. This supports findings from previous studies with AB participants. Fatigue properties were better in three of the four participants. The lower fatigue resistance with SDSS in one participant may be explained by a very low muscle activation level in this case. Further investigation in a larger cohort is warranted.

Stochastic stimulation has been shown to improve movement, balance, the sense of touch, and may also improve position sense. This stimulation can be non-invasive and may be a simple technology to enhance proprioception. In this study, we investigated whether sub-threshold stochastic tactile stimulation of mechanoreceptors reduces age-related errors in wrist position estimation. Fifteen young (24.5±1.5y) and 23 elderly (71.7±7.3y) unimpaired, right-handed adults completed a wrist position gauge-matching experiment. In each trial, the participant's concealed wrist was moved to a target position between 10 and 30° of wrist flexion or extension by a robotic manipulandum. The participant then estimated the wrist's position on a virtual gauge. During half of the trials, sub-threshold stochastic tactile stimulation was applied to the wrist muscle tendon areas. Stochastic stimulation did not significantly influence wrist position sense. In the elderly group, estimation errors decreased non-significantly when stimulation was applied compared to the trials without stimulation [mean constant error reduction Δμ(θconof)=0.8° in flexion and Δμ(θconoe)=0.7° in extension direction, p = 0.95]. This effect was less pronounced in the young group [Δμ(θcony)=0.2° in flexion and in extension direction, p = 0.99]. These improvements did not yield a relevant effect size (Cohen's d < 0.1). Estimation errors increased with target angle magnitude in both movement directions. In young participants, estimation errors were non-symmetric, with estimations in flexion [μ(θconyf)=1.8°, σ(θconyf)=7.0°] being significantly more accurate than in extension [μ(θconye)=8.3°, σ(θconye)=9.3°, p < 0.01]. This asymmetry was not present in the elderly group, where estimations in flexion [μ(θconof)=7.5°, σ(θconof)=9.8°] were similar to extension [μ(θconoe)=7.7°, σ(θconoe)=9.3°]. Hence, young and elderly participants performed equally in extension direction, whereas wrist position sense in flexion direction deteriorated with age (p < 0.01). Though unimpaired elderly adults did not benefit from stochastic stimulation, it cannot be deduced that individuals with more severe impairments of their sensory system do not profit from this treatment. While the errors in estimating wrist position are symmetric in flexion and extension in elderly adults, young adults are more accurate when estimating wrist flexion, an effect that has not been described before.

Abstract Background Multiplayer games have emerged as a promising approach to increase the motivation of patients involved in rehabilitation therapy. In this systematic review, we evaluated recent publications in health-related multiplayer games that involved patients with cognitive and/or motor impairments. The aim was to investigate the effect of multiplayer gaming on game experience and game performance in healthy and non-healthy populations in comparison to individual game play. We further discuss the publications within the context of the theory of flow and the challenge point framework. Methods A systematic search was conducted through EMBASE, Medline, PubMed, Cochrane, CINAHL and PsycINFO. The search was complemented by recent publications in robot-assisted multiplayer neurorehabilitation. The search was restricted to robot-assisted or virtual reality-based training. Results Thirteen articles met the inclusion criteria. Multiplayer modes used in health-related multiplayer games were: competitive, collaborative and co-active multiplayer modes. Multiplayer modes positively affected game experience in nine studies and game performance in six studies. Two articles reported increased game performance in single-player mode when compared to multiplayer mode. Conclusions The multiplayer modes of training reviewed improved game experience and game performance compared to single-player modes. However, the methods reviewed were quite heterogeneous and not exhaustive. One important take-away is that adaptation of the game conditions can individualize the difficulty of a game to a player’s skill level in competitive multiplayer games. Robotic assistance and virtual reality can enhance individualization by, for example, adapting the haptic conditions, e.g. by increasing haptic support or by providing haptic resistance. The flow theory and the challenge point framework support these results and are used in this review to frame the idea of adapting players’ game conditions.

Abstract Background Robots have been successfully applied in motor training during neurorehabilitation. As music is known to improve motor function and motivation in neurorehabilitation training, we aimed at integrating music creation into robotic-assisted motor therapy. We developed a virtual game-like environment with music for the arm therapy robot ARMin, containing four different motion training conditions: a condition promoting creativity (C+) and one not promoting creativity (C–), each in a condition with (V+) and without (V–) a visual display (i.e., a monitor). The visual display was presenting the game workspace but not contributing to the creative process itself. In all four conditions the therapy robot haptically displayed the game workspace. Our aim was to asses the effects of creativity and visual display on motivation. Methods In a prospective randomized single-center study, healthy participants were randomly assigned to play two of the four training conditions, either with (V+) or without visual display (V–). In the third round, the participants played a repetition of the preferred condition of the two first rounds, this time with a new V condition (i.e., with or without visual display). For each of the three rounds, motivation was measured with the Intrinsic Motivation Inventory (IMI) in the subscales interest/enjoyment, perceived choice, value/usefulness, and man-machine-relation. We recorded the actual training time, the time of free movement, and the velocity profile and administered a questionnaire to measure perceived training time and perceived effort. All measures were analysed using linear mixed models. Furthermore, we asked if the participants would like to receive the created music piece. Results Sixteen healthy subjects (ten males, six females, mean age: 27.2 years, standard deviation: 4.1 years) with no known motor or cognitive deficit participated. Promotion of creativity (i.e., C+ instead of C–) significantly increased the IMI-item interest/enjoyment (p=0.001) and the IMI-item perceived choice (p=0.010). We found no significant effects in the IMI-items man-machine relation and value/usefulness. Conditions promoting creativity (with or without visual display) were preferred compared to the ones not promoting creativity. An interaction effect of promotion of creativity and omission of visual display was present for training time (p=0.013) and training intensity (p

This narrative review provides a brief overview of the current literature on technology-based interventions for the neurorehabilitation of persons with Parkinson’s disease (PD). The role of brain–computer interfaces, exergaming/virtual-reality-based exercises, robot-assisted therapies and wearables is discussed. It is expected that technology-based neurorehabilitation will gain importance in the management of PD patients, although it is often not clear yet whether this approach is superior to conventional therapies. High-intensity technology-based neurorehabilitation may hold promise with respect to neuroprotective or neurorestorative actions in PD. Overall, more research is required in order to obtain more data on the feasibility, efficacy and safety of technology-based neurorehabilitation in persons with PD.

Abstract Impairment of neuromuscular function in neurological disorders leads to reductions in muscle force, which may lower quality of life. Rehabilitation robots that are equipped with sensors are able to quantify the extent of muscle force impairment and to monitor a patient during the process of neurorehabilitation with sensitive and objective assessment methods. In this article, we provide an overview of fundamental aspects of muscle function and how the corresponding variables can be quantified by means of meaningful robotic assessments that are primarily oriented towards upper limb neurorehabilitation. We discuss new concepts for the assessment of muscle function, and present an overview of the currently available systems for upper limb measurements. These considerations culminate in practical recommendations and caveats for the rational quantification of force magnitude, force direction, moment of a force, impulse, critical force (neuromuscular fatigue threshold) and state and trait levels of fatigue.

The original article contains an error in Fig 3f whereby data is erroneously extrapolated beyond 80 years of age; this also affects statements made elsewhere in the article.

Study ObjectivesGentle rocking movements provided by a moving bed have been proposed as a promising non-pharmacological way to promote sleep. In rodents the sleep promoting effect of rocking movements depended on the peak acceleration (named “stimulation intensity”) perceived by the vestibular system. We set out to verify previous reports on the sleep promoting effect of rocking movements and to investigate the importance of stimulation intensity in this process.MethodsSide-to-side rocking movements along a pendulum trajectory with different peak accelerations (control: 0 m/s2, low intensity: 0.15 m/s2, medium intensity: 0.25 m/s2, high intensity: 0.35 m/s2) were provided for 45 min during an afternoon nap opportunity. Participants were assigned to a low intensity group (n = 10) experiencing control, low and medium intensity stimulation or a high intensity group (n = 12) experiencing control, medium and high intensity stimulation. Sleep and sleep-related memory performance were assessed using polysomnography and a word-pair memory task, respectively.ResultsParticipants transitioned faster into deep sleep under the influence of medium intensity rocking as was evident by a faster buildup of delta power compared to the control condition (n = 22). The faster buildup did not affect sleep architecture, since e.g., the proportion of the nap spent in deep sleep or latencies did not change. Previously reported effects like a shorter latency to stage N2 and a higher density of sleep spindles were not observed. Sleep quality during control naps of the low intensity group was worse than in the high intensity group. In the low intensity group, we also observed a significant increase in delta power throughout the nap, as well as a higher density of slow oscillations both under the influence of low and medium intensity vestibular stimulation. No such effects were observed in the high intensity group.ConclusionRocking movements may promote nap sleep in young adults. Due to a difference in sleep quality during control naps between the low and high intensity group no conclusion regarding the influence of stimulation intensity were possible. Thus, optimal stimulation settings in humans need further investigation.

Background: Unlike other episodic sleep disorders in childhood, there are no agreed severity indices for rhythmic movement disorder. While movements can be characterized in detail by polysomnography, in our experience most children inhibit rhythmic movement during polysomnography. Actigraphy and home video allow assessment in the child’s own environment, but both have limitations. Standard actigraphy analysis algorithms fail to differentiate rhythmic movements from other movements. Manual annotation of 2D video is time consuming. We aimed to develop a sensitive, reliable method to detect and quantify rhythmic movements using marker free and automatic 3D video analysis.Method: Patients with rhythmic movement disorder (n = 6, 4 male) between age 5 and 14 years (M: 9.0 years, SD: 4.2 years) spent three nights in the sleep laboratory as part of a feasibility study (https://clinicaltrials.gov/ct2/show/NCT03528096). 2D and 3D video data recorded during the adaptation and baseline nights were analyzed. One ceiling-mounted camera captured 3D depth images, while another recorded 2D video. We developed algorithms to analyze the characteristics of rhythmic movements and built a classifier to distinguish between rhythmic and non-rhythmic movements based on 3D video data alone. Data from 3D automated analysis were compared to manual 2D video annotations to assess algorithm performance. Novel indices were developed, specifically the rhythmic movement index, frequency index, and duration index, to better characterize severity of rhythmic movement disorder in children.Result: Automatic 3D video analysis demonstrated high levels of agreement with the manual approach indicated by a Cohen’s kappa >0.9 and F1-score >0.9. We also demonstrated how rhythmic movement assessment can be improved using newly introduced indices illustrated with plots for ease of visualization.Conclusion: 3D video technology is widely available and can be readily integrated into sleep laboratory settings. Our automatic 3D video analysis algorithm yields reliable quantitative information about rhythmic movements, reducing the burden of manual scoring. Furthermore, we propose novel rhythmic movement disorder severity indices that offer a means to standardize measurement of this disorder in both clinical and research practice. The significance of the results is limited due to the nature of a feasibility study and its small number of samples. A larger follow up study is needed to confirm presented results.

Although robot-assisted training is present in various fields such as sports engineering and rehabilitation, provision of training strategies that optimally support individual motor learning remains as a challenge. Literature has shown that guidance strategies are useful for beginners, while skilled trainees should benefit from challenging conditions. The Challenge Point Theory also supports this in a way that learning is dependent on the available information, which serves as a challenge to the learner. So, learning can be fostered when the optimal amount of information is given according to the trainee's skill. Even though the framework explains the importance of difficulty modulation, there are no practical guidelines for complex dynamic tasks on how to match the difficulty to the trainee's skill progress. Therefore, the goal of this study was to determine the impact on learning of a complex motor task by a modulated task difficulty scheme during the training sessions, without distorting the nature of task. In this 3-day protocol study, we compared two groups of naïve participants for learning a sweep rowing task in a highly sophisticated rowing simulator. During trainings, groups received concurrent visual feedback displaying the requested oar movement. Control group performed the task under constant difficulty in the training sessions. Experimental group's task difficulty was modulated by changing the virtual water density that generated different heaviness of the simulated water-oar interaction, which yielded practice variability. Learning was assessed in terms of spatial and velocity magnitude errors and the variability for these metrics. Results of final day tests revealed that both groups reduced their error and variability for the chosen metrics. Notably, in addition to the provision of a very well established visual feedback and knowledge of results, experimental group's variable training protocol with modulated difficulty showed a potential to be advantageous for the spatial consistency and velocity accuracy. The outcomes of training and test runs indicate that we could successfully alter the performance of the trainees by changing the density value of the virtual water. Therefore, a follow-up study is necessary to investigate how to match different density values to the skill and performance improvement of the participants.

Lower limb exoskeletons require the correct support magnitude and timing to achieve user assistance. This study evaluated whether the sign of the angular velocity of lower limb segments can be used to determine the timing of the stance and the swing phase during walking. We assumed that stance phase is characterized by a positive, swing phase by a negative angular velocity. Thus, the transitions can be used to also identify heel-strike and toe-off. Thirteen subjects without gait impairments walked on a treadmill at speeds between 0.5 and 2.1 m/s on level ground and inclinations between −10 and +10°. Kinematic and kinetic data was measured simultaneously from an optical motion capture system, force plates, and five inertial measurement units (IMUs). These recordings were used to compute the angular velocities of four lower limb segments: two biological (thigh, shank) and two virtual that were geometrical projections of the biological segments (virtual leg, virtual extended leg). We analyzed the reliability (two sign changes of the angular velocity per stride) and the accuracy (offset in timing between sign change and ground reaction force based timing) of the virtual and biological segments for detecting the gait phases stance and swing. The motion capture data revealed that virtual limb segments seem superior to the biological limb segments in the reliability of stance and swing detection. However, increased signal noise when using the IMUs required additional rule sets for reliable stance and swing detection. With IMUs, the biological shank segment had the least variability in accuracy. The IMU-based heel-strike events of the shank and both virtual segment were slightly early (3.3–4.8% of the gait cycle) compared to the ground reaction force-based timing. Toe-off event timing showed more variability (9.0% too early to 7.3% too late) between the segments and changed with walking speed. The results show that the detection of the heel-strike, and thus stance phase, based on IMU angular velocity is possible for different segments when additional rule sets are included. Further work is required to improve the timing accuracy for the toe-off detection (swing).

Robotic algorithms that augment movement errors have been proposed as promising training strategies to enhance motor learning and neurorehabilitation. However, most research effort has focused on rehabilitation of upper limbs, probably because large movement errors are especially dangerous during gait training, as they might result in stumbling and falling. Furthermore, systematic large movement errors might limit the participants’ motivation during training. In this study, we investigated the effect of training with novel error modulating strategies, which guarantee a safe training environment, on motivation and learning of a modified asymmetric gait pattern. Thirty healthy young participants walked in the exoskeletal robotic system Lokomat while performing a foot target-tracking task, which required an increased hip and knee flexion in the dominant leg. Learning the asymmetric gait pattern with three different strategies was evaluated: (i) No disturbance: no robot disturbance/guidance was applied, (ii) haptic error amplification: unsafe and discouraging large errors were limited with haptic guidance, while haptic error amplification enhanced awareness of small errors relevant for learning, and (iii) visual error amplification: visually observed errors were amplified in a virtual reality environment. We also evaluated whether increasing the movement variability during training by adding randomly varying haptic disturbances on top of the other training strategies further enhances learning. We analyzed participants’ motor performance and self-reported intrinsic motivation before, during and after training. We found that training with the novel haptic error amplification strategy did not hamper motor adaptation and enhanced transfer of the practiced asymmetric gait pattern to free walking. Training with visual error amplification, on the other hand, increased errors during training and hampered motor learning. Participants who trained with visual error amplification also reported a reduced perceived competence. Adding haptic disturbance increased the movement variability during training, but did not have a significant effect on motor adaptation, probably because training with haptic disturbance on top of visual and haptic error amplification decreased the participants’ feelings of competence. The proposed novel haptic error modulating controller that amplifies small task-relevant errors while limiting large errors outperformed visual error augmentation and might provide a promising framework to improve robotic gait training outcomes in neurological patients.

Motor learning is assumed to be a partly error driven process. Motor learning studies on simple movements have shown that skilled subjects benefit from training with error amplification. Findings of studies with simple movements do not necessarily transfer to complex sport movements. The goal of this work was to determine the benefit of visual error amplification for non-naïve subjects in learning a fast rowing movement. We conducted a study comparing non-naïve subjects receiving a fading, visual feedback with visual error amplification against a control group receiving the same visual feedback without error amplification. Separate outcome metrics were applied for the domains of spatial and velocity magnitude errors. Besides error metrics, variability metrics were evaluated for both domains, such that they could be interpreted in quantitative relation to each other. The implemented error amplification did not cause group differences in any variable. Subjects with or without error amplification reached similar absolute levels in error and variability. Possible reasons remain speculative. For implementing error amplification to the training of complex movements design decisions must be made for which an informative basis is missing, e.g. the error amplification gains.

As the world’s population gradually grows older, more and more adults are experiencing sensory–motor disabilities due to stroke, traumatic brain injury, spinal cord injury and other diseases [...]

The classification of sleep stages is the first and an important step in the quantitative analysis of polysomnographic recordings. Sleep stage scoring relies heavily on visual pattern recognition by a human expert and is time consuming and subjective. Thus, there is a need for automatic classification. In this work we developed machine learning algorithms for sleep classification: random forest (RF) classification based on features and artificial neural networks (ANNs) working both with features and raw data. We tested our methods in healthy subjects and in patients. Most algorithms yielded good results comparable to human interrater agreement. Our study revealed that deep neural networks (DNNs) working with raw data performed better than feature-based methods. We also demonstrated that taking the local temporal structure of sleep into account a priori is important. Our results demonstrate the utility of neural network architectures for the classification of sleep.

Objective: Measurements of heart rate variability (HRV) during sleep have become increasingly popular as sleep could provide an optimal state for HRV assessments. While sleep stages have been reported to affect HRV, the effect of sleep stages on the variance of HRV parameters were hardly investigated. We aimed to assess the variance of HRV parameters during the different sleep stages. Further, we tested the accuracy of an algorithm using HRV to identify a 5-min segment within an episode of slow wave sleep (SWS, deep sleep).Methods: Polysomnographic (PSG) sleep recordings of 3 nights of 15 healthy young males were analyzed. Sleep was scored according to conventional criteria. HRV parameters of consecutive 5-min segments were analyzed within the different sleep stages. The total variance of HRV parameters was partitioned into between-subjects variance, between-nights variance, and between-segments variance and compared between the different sleep stages. Intra-class correlation coefficients of all HRV parameters were calculated for all sleep stages. To identify an SWS segment based on HRV, Pearson correlation coefficients of consecutive R-R intervals (rRR) of moving 5-min windows (20-s steps). The linear trend was removed from the rRR time series and the first segment with rRR values 0.1 units below the mean rRR for at least 10 min was identified. A 5-min segment was placed in the middle of such an identified segment and the corresponding sleep stage was used to assess the accuracy of the algorithm.Results: Good reproducibility within and across nights was found for heart rate in all sleep stages and for high frequency (HF) power in SWS. Reproducibility of low frequency (LF) power and of LF/HF was poor in all sleep stages. Of all the 5-min segments selected based on HRV data, 87% were accurately located within SWS.Conclusions: SWS, a stable state that, in contrast to waking, is unaffected by internal and external factors, is a reproducible state that allows reliable determination of heart rate, and HF power, and can satisfactorily be detected based on R-R intervals, without the need of full PSG. Sleep may not be an optimal condition to assess LF power and LF/HF power ratio.

Goal-directed reaching for real-world objects by humans is enabled through visual depth cues. In virtual environments, the number and quality of available visual depth cues is limited, which may affect reaching performance and quality of reaching movements.We assessed three-dimensional reaching movements in five experimental groups each with ten healthy volunteers. Three groups used a two-dimensional computer screen and two groups used a head-mounted display. The first screen group received the typically recreated visual depth cues, such as aerial and linear perspective, occlusion, shadows, and texture gradients. The second screen group received an abstract minimal rendering lacking those. The third screen group received the cues of the first screen group and absolute depth cues enabled by retinal image size of a known object, which realized with visual renderings of the handheld device and a ghost handheld at the target location. The two head-mounted display groups received the same virtually recreated visual depth cues as the second or the third screen group respectively. Additionally, they could rely on stereopsis and motion parallax due to head-movements.All groups using the screen performed significantly worse than both groups using the head-mounted display in terms of completion time normalized by the straight-line distance to the target. Both groups using the head-mounted display achieved the optimal minimum in number of speed peaks and in hand path ratio, indicating that our subjects performed natural movements when using a head-mounted display. Virtually recreated visual depth cues had a minor impact on reaching performance. Only the screen group with rendered handhelds could outperform the other screen groups. Thus, if reaching performance in virtual environments is in the main scope of a study, we suggest applying a head-mounted display. Otherwise, when two-dimensional screens are used, achievable performance is likely limited by the reduced depth perception and not just by subjects' motor skills.

This paper presents a new approach to benchmarking brain-computer interfaces (BCIs) outside the lab. A computer game was created that mimics a real-world application of assistive BCIs, with the main outcome metric being the time needed to complete the game. This approach was used at the Cybathlon 2016, a competition for people with disabilities who use assistive technology to achieve tasks. The paper summarizes the technical challenges of BCIs, describes the design of the benchmarking game, then describes the rules for acceptable hardware, software and inclusion of human pilots in the BCI competition at the Cybathlon. The 11 participating teams, their approaches, and their results at the Cybathlon are presented. Though the benchmarking procedure has some limitations (for instance, we were unable to identify any factors that clearly contribute to BCI performance), it can be successfully used to analyze BCI performance in realistic, less structured conditions. In the future, the parameters of the benchmarking game could be modified to better mimic different applications (e.g., the need to use some commands more frequently than others). Furthermore, the Cybathlon has the potential to showcase such devices to the general public.

Muscle weakness—which can result from neurological injuries, genetic disorders, or typical aging—can affect a person's mobility and quality of life. For many people with muscle weakness, assistive devices provide the means to regain mobility and independence. These devices range from well-established technology, such as wheelchairs, to newer technologies, such as exoskeletons and exosuits. For assistive devices to be used in everyday life, they must provide assistance across activities of daily living (ADLs) in an unobtrusive manner. This article introduces the Myosuit, a soft, wearable device designed to provide continuous assistance at the hip and knee joint when working with and against gravity in ADLs. This robotic device combines active and passive elements with a closed-loop force controller designed to behave like an external muscle (exomuscle) and deliver gravity compensation to the user. At 4.1 kg (4.6 kg with batteries), the Myosuit is one of the lightest untethered devices capable of delivering gravity support to the user's knee and hip joints. This article presents the design and control principles of the Myosuit. It describes the textile interface, tendon actuators, and a bi-articular, synergy-based approach for continuous assistance. The assistive controller, based on bi-articular force assistance, was tested with a single subject who performed sitting transfers, one of the most gravity-intensive ADLs. The results show that the control concept can successfully identify changes in the posture and assist hip and knee extension with up to 26% of the natural knee moment and up to 35% of the knee power. We conclude that the Myosuit's novel approach to assistance using a bi-articular architecture, in combination with the posture-based force controller, can effectively assist its users in gravity-intensive ADLs, such as sitting transfers.

Up to date, the functional gains obtained after robot-aided gait rehabilitation training are limited. Error augmenting strategies have a great potential to enhance motor learning of simple motor tasks. However, little is known about the effect of these error modulating strategies on complex tasks, such as relearning to walk after a neurologic accident. Additionally, neuroimaging evaluation of brain regions involved in learning processes could provide valuable information on behavioral outcomes. We investigated the effect of robotic training strategies that augment errors—error amplification and random force disturbance—and training without perturbations on brain activation and motor learning of a complex locomotor task. Thirty-four healthy subjects performed the experiment with a robotic stepper (MARCOS) in a 1.5 T MR scanner. The task consisted in tracking a Lissajous figure presented on a display by coordinating the legs in a gait-like movement pattern. Behavioral results showed that training without perturbations enhanced motor learning in initially less skilled subjects, while error amplification benefited better-skilled subjects. Training with error amplification, however, hampered transfer of learning. Randomly disturbing forces induced learning and promoted transfer in all subjects, probably because the unexpected forces increased subjects' attention. Functional MRI revealed main effects of training strategy and skill level during training. A main effect of training strategy was seen in brain regions typically associated with motor control and learning, such as, the basal ganglia, cerebellum, intraparietal sulcus, and angular gyrus. Especially, random disturbance and no perturbation lead to stronger brain activation in similar brain regions than error amplification. Skill-level related effects were observed in the IPS, in parts of the superior parietal lobe (SPL), i.e., precuneus, and temporal cortex. These neuroimaging findings indicate that gait-like motor learning depends on interplay between subcortical, cerebellar, and fronto-parietal brain regions. An interesting observation was the low activation observed in the brain's reward system after training with error amplification compared to training without perturbations. Our results suggest that to enhance learning of a locomotor task, errors should be augmented based on subjects' skill level. The impacts of these strategies on motor learning, brain activation, and motivation in neurological patients need further investigation.

Research on motor learning suggests that training with haptic guidance enhances learning of the timing components of motor tasks, whereas error amplification is better for learning the spatial components. We present a novel mixed guidance controller that combines haptic guidance and error amplification to simultaneously promote learning of the timing and spatial components of complex motor tasks. The controller is realized using a force field around the desired position. This force field has a stable manifold tangential to the trajectory that guides subjects in velocity-related aspects. The force field has an unstable manifold perpendicular to the trajectory, which amplifies the perpendicular (spatial) error. We also designed a controller that applies randomly varying, unpredictable disturbing forces to enhance the subjects’ active participation by pushing them away from their “comfort zone.” We conducted an experiment with thirty-two healthy subjects to evaluate the impact of four different training strategies on motor skill learning and self-reported motivation: (i) No haptics, (ii) mixed guidance, (iii) perpendicular error amplification and tangential haptic guidance provided in sequential order, and (iv) randomly varying disturbing forces. Subjects trained two motor tasks using ARMin IV, a robotic exoskeleton for upper limb rehabilitation: follow circles with an ellipsoidal speed profile, and move along a 3D line following a complex speed profile. Mixed guidance showed no detectable learning advantages over the other groups. Results suggest that the effectiveness of the training strategies depends on the subjects’ initial skill level. Mixed guidance seemed to benefit subjects who performed the circle task with smaller errors during baseline (i.e., initially more skilled subjects), while training with no haptics was more beneficial for subjects who created larger errors (i.e., less skilled subjects). Therefore, perhaps the high functional difficulty of the tasks limited the potential benefit of mixed guidance. Adding random disturbing forces during training reduced the learning effect size compared to no haptics. The unanticipated forces also decreased the subjects’ feelings of competence while did not increase their effort and interest. Further studies with mildly affected neurologically patients employing easier tasks need to be performed in order to evaluate the applicability of our approaches in rehabilitation.

Introduction: Robot-assisted tilt table therapy was proposed for early rehabilitation and mobilization of patients after diseases such as stroke. A robot-assisted tilt table with integrated passive robotic leg exercise (PE) mechanism has the potential to prevent orthostatic hypotension usually provoked by verticalization. In a previous study with rather young healthy subjects [average age: 25.1 ± 2.6 years (standard deviation)], we found that PE effect on the cardiovascular system depends on the verticalization angle of the robot-assisted tilt table. In the current study, we investigated in an older population of neurological patients (a) whether they show the same PE effects as younger healthy population on the cardiovascular system at different tilt angles, (b) whether changing the PE frequency (i.e., stepping speed) influences the PE effect on the cardiovascular system, (c) whether PE could prevent orthostatic hypotension, and finally, (d) whether PE effect is consistent from day to day.Methods: Heart rate (HR), and systolic and diastolic blood pressures (sBP, dBP) in response to PE at two different tilt angles (α = 20°, 60°) with three different PE frequencies (i.e., 0, 24, and 48 steps per minute) of 10 neurological patients [average age: 68.4 ± 13.5 years (standard deviation)] were measured on 2 consecutive days. Linear mixed models were used to develop statistical models and analyze the repeated measurements.Results: The models show that: PE significantly increased sBP and dBP but had no significant effect on HR. (a) Similar to healthy subjects the effect of PE on sBP was dependent on the tilt angle with higher tilt angles resulting in a higher increase. Head-up tilting alone significantly increased HR and dBP but resulted in a non-significant drop in sBP. PE, in general, had a more additive effect on increasing BP. (b) The effect of PE was not influenced by its speed. (c) Neither during head-up tilt alone nor in combination with PE did participants experience orthostatic hypotension. (d) The measurement day was not a statistically significant factor regarding the effects of verticalization and PE on the cardiovascular response.Conclusion: We provide evidence that PE can increase steady-state values of sBP and dBP in neurological patients during head-up tilt. Similar to healthy subjects the effect on sBP depends on the verticalization angle of the robot-assisted tilt table. PE might have the potential to prevent orthostatic hypotension, but as the amount of drop in BP in response to head-up tilting was not leading to orthostatic hypotension in our patients, we could neither conclude nor reject such a preventive compensatory effect. Furthermore, we found that changing the PE speed does not influence the steady-state cardiovascular response.

Tilt tables enable early mobilization of patients by providing verticalization. But there is a high risk of orthostatic hypotension provoked by verticalization, especially after neurological diseases such as spinal cord injury. Robot-assisted tilt tables might be an alternative as they add passive robotic leg exercise (PE) that can be enhanced with functional electrical stimulation (FES) to the verticalization, thus reducing the risk of orthostatic hypotension. We hypothesized that the influence of PE on the cardiovascular system during verticalization depends on the verticalization angle, and FES strengthens the PE influence. To test our hypotheses, we investigated the PE effects on the cardiovascular parameters heart rate (HR), and systolic and diastolic blood pressures (sBP, dBP) at different angles of verticalization in a healthy population. Ten healthy subjects on a robot-assisted tilt table underwent four different study protocols while HR, sBP and dBP were measured: (1) head-up tilt to 60° and 71° without PE; (2) PE at 20°, 40°, and 60° of head-up tilt; (3) PE while constant FES intensity was applied to the leg muscles, at 20°, 40°, and 60° of head-up tilt; (4) PE with variation of the applied FES intensity at 0°, 20°, 40°, and 60° of head-up tilt. Linear mixed models were used to model changes in HR, sBP, and dBP responses. The models show that: (1) head-up tilt alone resulted in statistically significant increases in HR and dBP, but no change in sBP. (2) PE during head-up tilt resulted in statistically significant changes in HR, sBP, and dBP, but not at each angle and not always in the same direction (i.e., increase or decrease of cardiovascular parameters). Neither adding (3) FES at constant intensity to PE nor (4) variation of FES intensity during PE had any statistically significant effects on the cardiovascular parameters.The effect of PE on the cardiovascular system during head-up tilt is strongly dependent on the verticalization angle. Therefore, we conclude that orthostatic hypotension cannot be prevented by PE alone, but that the preventive effect depends on the verticalization angle. FES is not an important contributing factor.

Rehabilitation robots have become important tools in stroke rehabilitation. Compared to manual arm training, robot-supported training can be more intensive, of longer duration and more repetitive. Therefore, robots have the potential to improve the rehabilitation process in stroke patients. Whereas a majority of previous work in upper limb rehabilitation robotics has focused on end-effector-based robots, a shift towards exoskeleton robots is taking place because they offer a better guidance of the human arm, especially for movements with a large range of motion. However, the implementation of an exoskeleton device introduces the challenge of reproducing the motion of the human shoulder, which is one of the most complex joints of the body. Thus, this paper starts with describing a simplified model of the human shoulder. On the basis of that model, a new ergonomic shoulder actuation principle that provides motion of the humerus head is proposed, and its implementation in the ARMin III arm therapy robot is described. The focus lies on the mechanics and actuation principle. The ARMin III robot provides three actuated degrees of freedom for the shoulder and one for the elbow joint. An additional module provides actuated lower arm pro/supination and wrist flexion/extension. Five ARMin III devices have been manufactured and they are currently undergoing clinical evaluation in hospitals in Switzerland and in the United States.

For centuries, rocking has been used to promote sleep in babies or toddlers. Recent research suggested that relaxation could play a role in facilitating the transition from waking to sleep during rocking. Breathing techniques are often used to promote relaxation. However, studies investigating head motions and body rotations showed that vestibular stimulation might elicit a vestibulo-respiratory response, leading to an increase in respiration frequency. An increase in respiration frequency would not be considered to promote relaxation in the first place. On the other hand, a coordination of respiration to rhythmic vestibular stimulation has been observed. Therefore, this study aimed to investigate the effect of different movement frequencies and amplitudes on respiration frequency. Furthermore, we tested whether subjects adapt their respiration to movement frequencies below their spontaneous respiration frequency at rest, which could be beneficial for relaxation. Twenty-one healthy subjects (24-42 years, 12 males) were investigated using an actuated bed, moving along a lateral translation. Following movement frequencies were applied: +30%, +15%, -15%, and -30% of subjects' rest respiration frequency during baseline (no movement). Furthermore, two different movement amplitudes were tested (Amplitudes: 15 cm, 7.5 cm; movement frequency: 0.3 Hz). In addition, five subjects (25-28 years, 2 males) were stimulated with their individual rest respiration frequency. Rocking movements along a lateral translation caused a vestibulo-respiratory adaptation leading to an increase in respiration frequency. The increase was independent of the applied movement frequencies or amplitudes but did not occur when stimulating with subjects' rest respiration frequency. Furthermore, no synchronization of the respiration frequency to the movement frequency was observed. In particular, subjects did not lower their respiration frequency below their resting frequency. Hence, it was not feasible to influence respiration in a manner that might be considered beneficial for relaxation.